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Record W4391313144 · doi:10.1103/physrevd.109.023532

Can prompt cusps of WIMP dark matter be detected as individual gamma-ray sources?

2024· article· en· W4391313144 on OpenAlexfundno aff
M. Délos

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueOntario Ministry of Research, Innovation and ScienceGovernment of CanadaInnovation, Science and Economic Development Canada
KeywordsWIMPPhysicsDark matterGamma rayCosmic rayNuclear physicsAstrophysics

Abstract

fetched live from OpenAlex

Prompt $\ensuremath{\rho}\ensuremath{\propto}{r}^{\ensuremath{-}1.5}$ density cusps are the densest and most abundant dark matter systems. If the dark matter is a weakly interacting massive particle (WIMP), recent studies have shown that prompt cusps dominate the aggregate dark matter annihilation rate. This article explores whether individual prompt cusps could be detected as gamma-ray sources. At the Fermi Telescope's point-source sensitivity, WIMPs with the canonical annihilation cross section could form detectable prompt cusps if the particle mass is of order 10 GeV. These objects could be 10--100 pc away and weigh under a solar mass; they would subtend around 0.1 degrees on the sky. For GeV-scale dark matter particles with below-canonical cross sections, searches for individual prompt cusps can be more sensitive than searches for the annihilation signals from galactic dark matter halos.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.360
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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